The parameter identification using artificial neural networks is becoming very popular. In this chapter, the parameters of dynamical system are identified using artificial neural networks. A fast gradient decent technique for the parameter identification of a linear dynamical system has been...

Numerous techniques have been used to identify flow regimes and liquid holdup in horizontal multiphase flow, but often neither perform well nor very accurate. Recently, neuro-fuzzy inference systems learning scheme have been gaining popularity in its capability for solving both prediction and...

An existing low complexity, black box artificial neural network model (ANN model) is investigated towards its more general applicability in the field of high isobaric–isothermal inactivation of enzymes. The use of this non-linear modeling technique makes it possible to describe accurately...

Water quantity and quality are considered to be the main driving forces of the reservoir operation. Barra Bonita reservoir, located in the southeast region of Brazil, is chosen as the case study for the application of the proposed methodology. Herein, optimization and artificial intelligence...

Two new methods to identify the mechanical parameters in induction motor based field oriented drives are presented in this paper. The identified parameters are: the moment of inertia and the viscous damping coefficient. The proposed methods are based on the adaptive linear neuron (ADALINE)...